Systems AI Engineer

Why This Role Exists

Most systems work at a low scale. Very few survive real production load, complex workflows, and enterprise edge cases.

We are building a platform that must:

• Scale from 500K to 20M+ interactions per month.
• Handle complex insurance workflows reliably.
• Become easier to deploy as it grows, not harder.

This role exists to build the backend foundation that makes this possible.

What You'll Do

You will not just write services. You will design and own core platform systems.

1. Scale the Platform Without Breaking Architecture

Scale from 50K to 4M+ interactions per month.

Ensure:

• High availability.
• Low latency.
• Fault tolerance.
• Clean architectural evolution without requiring large rewrites.

2. Build the Workflow Automation (WA) Engine

Design a flexible system that supports:

• States.
• Stages.
• Cohorts.
• Dynamic workflows.

Ensure workflows:

• Handle edge cases reliably.
• Can be configured easily.
• Move from hardcoded flows to a configurable execution engine.

3. Build the Insurance-Specific Data Layer

Design data models for:

• Policy states.
• Claim workflows.
• Consent tracking.

Ensure the system works across:

• Multiple insurers.
• Multiple use cases.

Build a platform-first data layer, not a collection of use-case-specific hacks.

4. Make Deployment and Setup Simple

Ensure workflows and data models are:

• Easy to configure.
• Easy to launch.

Reduce friction for:

• Product teams.
• Deployment teams.

5. Create a Compounding Data Advantage

Build a data layer that:

• Improves with every deployment.
• Captures structured signals.

Ensure data becomes a long-term competitive advantage, not just storage.

6. Own Production Reliability

Participate in an on-call rotation across a team of three engineers.

Ensure:

• Incidents are handled quickly.
• Root causes are fixed permanently.
• Reliability is shared across the team, not dependent on individuals.

What Success Looks Like

• The platform scales to 2M+ interactions per month smoothly.
• The workflow engine supports complex, dynamic use cases.
• The data layer enables fast deployment across accounts.
• Edge cases are handled without constant firefighting.
• The system becomes easier to use as it grows.
• Production issues are rare and predictable.

Who You Are

You have built:

• Scalable systems.
• Distributed services.

You think in terms of:

• Systems.
• Data models.
• Trade-offs.

You are comfortable owning:

• Architecture.
• Production systems.

What Will Make You Stand Out

Experience building:

• Workflow engines.
• State machines.
• Data-heavy platforms.

Strong understanding of:

• System design.
• Distributed systems.
• Failure handling.

Experience working in:

• High-scale production environments.

Why Join?

You will build the core backend of an AI platform.

Your work directly impacts:

• Scale.
• Reliability.
• Product capability.

You will design systems that evolve from use-case-specific implementations to platform-level infrastructure.

What This Role Is Not

• Not just API development.
• Not limited to feature-level work.
• Not disconnected from production realities.

What This Role Is

• A system architect.
• A builder of scalable platforms.
• A driver of long-term technical advantage.

One Question to Self-Evaluate

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow?